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What software to use to build a graph based on microarray gene expression mutual correlation?

I have tried Cytoscape`s Reactome FI and a recipe from R bioinformatics cookbook, however, need a more reliable robust software or R/Python tutorial on how to make a graph with gene-nodes and edges built on the rule of significant (p<0,05) positive and negative Pearson/Spearman correlations.

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    $\begingroup$ do you have any examples of similar graphs - perhaps an illustrative example could help (draw one in powerpoint and save it as an image) plus some idea of the data, and what you are trying to show $\endgroup$ – rg255 Jan 29 '15 at 8:55
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    $\begingroup$ I'm voting to close this question as off-topic because this is not related to biology but is basically about how to visualize a graph/network. How to build gene networks from expression data is still a valid question but that is not what is asked. $\endgroup$ – WYSIWYG Feb 26 '15 at 9:23
  • $\begingroup$ Hi @VassiaAlk - Cytoscape is pretty well designed for constructing a "network" of genes that are connected by their degree of correlation in expression; check out the online resources (e.g. apps.cytoscape.org/apps/expressioncorrelation). This site is aimed at biological questions, therefore this is off topic. Best $\endgroup$ – Luke Feb 26 '15 at 10:22

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